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<div class="title">Winograd.cpp File Reference</div>  </div>
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<div class="textblock"><code>#include &quot;<a class="el" href="_c_l_winograd_filter_transform_kernel_8h_source.xhtml">arm_compute/core/CL/kernels/CLWinogradFilterTransformKernel.h</a>&quot;</code><br />
<code>#include &quot;<a class="el" href="_c_l_winograd_output_transform_kernel_8h_source.xhtml">arm_compute/core/CL/kernels/CLWinogradOutputTransformKernel.h</a>&quot;</code><br />
<code>#include &quot;<a class="el" href="arm__compute_2core_2_types_8h_source.xhtml">arm_compute/core/Types.h</a>&quot;</code><br />
<code>#include &quot;<a class="el" href="_shape_calculator_8h_source.xhtml">arm_compute/core/utils/misc/ShapeCalculator.h</a>&quot;</code><br />
<code>#include &quot;<a class="el" href="_c_l_tensor_8h_source.xhtml">arm_compute/runtime/CL/CLTensor.h</a>&quot;</code><br />
<code>#include &quot;<a class="el" href="_c_l_tensor_allocator_8h_source.xhtml">arm_compute/runtime/CL/CLTensorAllocator.h</a>&quot;</code><br />
<code>#include &quot;<a class="el" href="_c_l_winograd_convolution_layer_8h_source.xhtml">arm_compute/runtime/CL/functions/CLWinogradConvolutionLayer.h</a>&quot;</code><br />
<code>#include &quot;<a class="el" href="_c_l_winograd_input_transform_8h_source.xhtml">arm_compute/runtime/CL/functions/CLWinogradInputTransform.h</a>&quot;</code><br />
<code>#include &quot;<a class="el" href="_c_l_accessor_8h_source.xhtml">tests/CL/CLAccessor.h</a>&quot;</code><br />
<code>#include &quot;<a class="el" href="_c_l_2_helper_8h_source.xhtml">tests/CL/Helper.h</a>&quot;</code><br />
<code>#include &quot;<a class="el" href="_padding_calculator_8h_source.xhtml">tests/PaddingCalculator.h</a>&quot;</code><br />
<code>#include &quot;tests/datasets/LargeConvolutionLayerDataset.h&quot;</code><br />
<code>#include &quot;tests/datasets/ShapeDatasets.h&quot;</code><br />
<code>#include &quot;tests/datasets/SmallConvolutionLayerDataset.h&quot;</code><br />
<code>#include &quot;tests/datasets/WinogradInputTransformDataset.h&quot;</code><br />
<code>#include &quot;tests/datasets/WinogradOutputTransformDataset.h&quot;</code><br />
<code>#include &quot;<a class="el" href="_asserts_8h_source.xhtml">tests/framework/Asserts.h</a>&quot;</code><br />
<code>#include &quot;<a class="el" href="tests_2framework_2_macros_8h_source.xhtml">tests/framework/Macros.h</a>&quot;</code><br />
<code>#include &quot;<a class="el" href="_datasets_8h_source.xhtml">tests/framework/datasets/Datasets.h</a>&quot;</code><br />
<code>#include &quot;<a class="el" href="_validation_8h_source.xhtml">tests/validation/Validation.h</a>&quot;</code><br />
<code>#include &quot;tests/validation/fixtures/WinogradConvolutionLayerFixture.h&quot;</code><br />
</div>
<p><a href="_c_l_2_winograd_8cpp_source.xhtml">Go to the source code of this file.</a></p>
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<tr class="memitem:a9de169e4fa76234b647b2454f662fd22"><td class="memItemLeft" align="right" valign="top">using&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation.xhtml#a9de169e4fa76234b647b2454f662fd22">CLWinogradInputTransformFixture</a> = WinogradInputTransformValidationFixture&lt; CLTensor, CLAccessor, CLWinogradInputTransform, float &gt;</td></tr>
<tr class="separator:a9de169e4fa76234b647b2454f662fd22"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a054857a13b43100f3d48e98e7a4cb626"><td class="memItemLeft" align="right" valign="top">using&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation.xhtml#a054857a13b43100f3d48e98e7a4cb626">CLWinogradFilterTransform</a> = CLSynthetizeFunctionWithZeroConstantBorder&lt; CLWinogradFilterTransformKernel, 0 &gt;</td></tr>
<tr class="separator:a054857a13b43100f3d48e98e7a4cb626"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a65565dedbc30c8ef560356c4a25e80dc"><td class="memItemLeft" align="right" valign="top">using&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation.xhtml#a65565dedbc30c8ef560356c4a25e80dc">CLWinogradFilterTransformFixture</a> = WinogradFilterTransformValidationFixture&lt; CLTensor, CLAccessor, CLWinogradFilterTransform, float &gt;</td></tr>
<tr class="separator:a65565dedbc30c8ef560356c4a25e80dc"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a2dd717bab37b161a6c1e63a76549d024"><td class="memItemLeft" align="right" valign="top">using&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation.xhtml#a2dd717bab37b161a6c1e63a76549d024">CLWinogradOutputTransform</a> = CLSynthetizeFunctionWithZeroConstantBorder&lt; CLWinogradOutputTransformKernel, 0 &gt;</td></tr>
<tr class="separator:a2dd717bab37b161a6c1e63a76549d024"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a9786317f3c3123dc0d609fd3e791d220"><td class="memItemLeft" align="right" valign="top">using&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation.xhtml#a9786317f3c3123dc0d609fd3e791d220">CLWinogradOutputTransformFixture</a> = WinogradOutputTransformValidationFixture&lt; CLTensor, CLAccessor, CLWinogradOutputTransform, float &gt;</td></tr>
<tr class="separator:a9786317f3c3123dc0d609fd3e791d220"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a4aa7763717f234371acad168e9ed5e5f"><td class="memItemLeft" align="right" valign="top">using&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation.xhtml#a4aa7763717f234371acad168e9ed5e5f">CLWinogradConvolutionLayerFastMathFixture</a> = WinogradConvolutionLayerFastMathValidationFixture&lt; CLTensor, CLAccessor, CLWinogradConvolutionLayer, float &gt;</td></tr>
<tr class="separator:a4aa7763717f234371acad168e9ed5e5f"><td class="memSeparator" colspan="2">&#160;</td></tr>
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<tr class="memitem:a273a18c5a1ff725a1f3ba44fab48f188"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation.xhtml#a273a18c5a1ff725a1f3ba44fab48f188">DATA_TEST_CASE</a> (Validate, framework::DatasetMode::ALL, zip(zip(zip(framework::dataset::make(&quot;InputInfo&quot;,{TensorInfo(TensorShape(53U, 21U, 5U, 3U), 1, DataType::F16), TensorInfo(TensorShape(53U, 21U, 5U, 3U), 1, DataType::QASYMM8), TensorInfo(TensorShape(53U, 21U, 5U, 3U), 1, DataType::F32), TensorInfo(TensorShape(53U, 21U, 5U, 3U), 1, DataType::F32), TensorInfo(TensorShape(53U, 33U, 4U), 1, DataType::F32), TensorInfo(TensorShape(34U, 42U, 7U, 3U), 1, DataType::F32), TensorInfo(TensorShape(31U, 37U, 37U), 1, DataType::F32)}), framework::dataset::make(&quot;OutputInfo&quot;,{TensorInfo(TensorShape(5U, 5U, 16U, 3U), 1, DataType::F16), TensorInfo(TensorShape(5U, 5U, 16U, 3U), 1, DataType::QASYMM8), TensorInfo(TensorShape(5U, 5U, 16U, 3U), 1, DataType::F32), TensorInfo(TensorShape(5U, 1U, 16U, 3U), 1, DataType::F32), TensorInfo(TensorShape(4U, 442U, 16U), 1, DataType::F32), TensorInfo(TensorShape(7U, 320U, 16U, 3U), 1, DataType::F32), TensorInfo(TensorShape(37U, 304U, 16U), 1, DataType::F32)})), framework::dataset::make(&quot;WinogradInfo&quot;,{WinogradInfo(Size2D(2, 2), Size2D(3, 3), Size2D(53U, 21U), PadStrideInfo(1, 1, 1, 0), DataLayout::NCHW), WinogradInfo(Size2D(2, 2), Size2D(3, 3), Size2D(53U, 21U), PadStrideInfo(1, 1, 0, 0), DataLayout::NCHW), WinogradInfo(Size2D(2, 2), Size2D(3, 3), Size2D(53U, 21U), PadStrideInfo(1, 1, 1, 1), DataLayout::NCHW), WinogradInfo(Size2D(2, 2), Size2D(3, 3), Size2D(53U, 21U), PadStrideInfo(2, 1, 1, 1), DataLayout::NCHW), WinogradInfo(Size2D(2, 2), Size2D(3, 3), Size2D(53U, 33U), PadStrideInfo(1, 1, 0, 1), DataLayout::NCHW), WinogradInfo(Size2D(2, 2), Size2D(3, 3), Size2D(34U, 42U), PadStrideInfo(1, 1, 0, 0), DataLayout::NCHW), WinogradInfo(Size2D(2, 2), Size2D(3, 3), Size2D(31U, 37U), PadStrideInfo(1, 1, 1, 1), DataLayout::NCHW)})), framework::dataset::make(&quot;Expected&quot;,{false, false, false, false, false, false, false})), input_info, output_info, winograd_info, expected)</td></tr>
<tr class="separator:a273a18c5a1ff725a1f3ba44fab48f188"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a1c070c74e504059d7c7f78219cd5c3e1"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation.xhtml#a1c070c74e504059d7c7f78219cd5c3e1">DATA_TEST_CASE</a> (Configuration, framework::DatasetMode::ALL, combine(combine(framework::dataset::concat(datasets::SmallWinogradInputTransformDataset(), datasets::LargeWinogradInputTransformDataset()), framework::dataset::make(&quot;DataLayout&quot;,{DataLayout::NCHW})), framework::dataset::make(&quot;DataType&quot;,{DataType::F32})), shape_in, winograd_info, data_layout, data_type)</td></tr>
<tr class="separator:a1c070c74e504059d7c7f78219cd5c3e1"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aef9276589f6bff9aafd338b52dcaa1f7"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation.xhtml#aef9276589f6bff9aafd338b52dcaa1f7">FIXTURE_DATA_TEST_CASE</a> (RunSmall, CLWinogradInputTransformFixture, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallWinogradInputTransformDataset(), framework::dataset::make(&quot;DataLayout&quot;,{DataLayout::NCHW})), framework::dataset::make(&quot;DataType&quot;,{DataType::F32})))</td></tr>
<tr class="separator:aef9276589f6bff9aafd338b52dcaa1f7"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a887aea07c914a0229495892d25389be7"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation.xhtml#a887aea07c914a0229495892d25389be7">FIXTURE_DATA_TEST_CASE</a> (RunLarge, CLWinogradInputTransformFixture, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeWinogradInputTransformDataset(), framework::dataset::make(&quot;DataLayout&quot;,{DataLayout::NCHW})), framework::dataset::make(&quot;DataType&quot;,{DataType::F32})))</td></tr>
<tr class="separator:a887aea07c914a0229495892d25389be7"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a38fe4b20a05bbaa1c844f3d7a19791ae"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation.xhtml#a38fe4b20a05bbaa1c844f3d7a19791ae">TEST_SUITE_END</a> () <a class="el" href="tests_2validation_2_u_n_i_t_2_utils_8cpp.xhtml#a9e461b3ac0012c8c7193c1e180c91f67">DATA_TEST_CASE</a>(Configuration = ConvolutionSeparableValidationFixture&lt;CLTensor, CLAccessor, CLConvolution5x5, T&gt;</td></tr>
<tr class="separator:a38fe4b20a05bbaa1c844f3d7a19791ae"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:af2041055b792c65741e6df32abd58177"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation.xhtml#af2041055b792c65741e6df32abd58177">zip</a> (zip(zip(framework::dataset::make(&quot;InputInfo&quot;,{TensorInfo(TensorShape(3U, 3U, 5U, 3U), 1, DataType::F16), TensorInfo(TensorShape(3U, 3U, 5U, 3U), 1, DataType::QASYMM8), TensorInfo(TensorShape(5U, 5U, 5U, 3U), 1, DataType::F32), TensorInfo(TensorShape(3U, 3U), 1, DataType::F32), TensorInfo(TensorShape(3U, 3U, 5U, 3U), 1, DataType::F32), TensorInfo(TensorShape(3U, 3U, 37U, 2U), 1, DataType::F32), TensorInfo(TensorShape(3U, 3U, 37U, 22U), 1, DataType::F32)}), framework::dataset::make(&quot;OutputInfo&quot;,{TensorInfo(TensorShape(3U, 5U, 16U), 1, DataType::F16), TensorInfo(TensorShape(3U, 5U, 16U), 1, DataType::QASYMM8), TensorInfo(TensorShape(3U, 5U, 16U), 1, DataType::F32), TensorInfo(TensorShape(1U, 1U, 16U), 1, DataType::F32), TensorInfo(TensorShape(3U, 5U, 16U), 1, DataType::F32), TensorInfo(TensorShape(2U, 37U, 16U), 1, DataType::F32), TensorInfo(TensorShape(22U, 37U, 36U), 1, DataType::F32)})), framework::dataset::make(&quot;WinogradInfo&quot;,{WinogradInfo(Size2D(2U, 2U), Size2D(3U, 3U), Size2D(), PadStrideInfo(), DataLayout::NCHW), WinogradInfo(Size2D(2U, 2U), Size2D(3U, 3U), Size2D(), PadStrideInfo(), DataLayout::NCHW), WinogradInfo(Size2D(2U, 2U), Size2D(3U, 3U), Size2D(), PadStrideInfo(), DataLayout::NCHW), WinogradInfo(Size2D(3U, 3U), Size2D(3U, 3U), Size2D(), PadStrideInfo(), DataLayout::NCHW), WinogradInfo(Size2D(2U, 2U), Size2D(3U, 3U), Size2D(), PadStrideInfo(), DataLayout::NCHW), WinogradInfo(Size2D(2U, 2U), Size2D(3U, 3U), Size2D(), PadStrideInfo(), DataLayout::NCHW), WinogradInfo(Size2D(4U, 4U), Size2D(3U, 3U), Size2D(), PadStrideInfo(), DataLayout::NCHW)})), framework::dataset::make(&quot;Expected&quot;,{false, false, false, false, true, true, true}))</td></tr>
<tr class="separator:af2041055b792c65741e6df32abd58177"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aee2a24d28b5b24452c348a21f156c83b"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation.xhtml#aee2a24d28b5b24452c348a21f156c83b">DATA_TEST_CASE</a> (Configuration, framework::DatasetMode::ALL, combine(combine(combine(framework::dataset::concat(datasets::Small3x3Shapes(), datasets::Large3x3Shapes()), framework::dataset::make(&quot;OutputTile&quot;,{Size2D(2U, 2U), Size2D(4U, 4U)})), framework::dataset::make(&quot;DataLayout&quot;,{DataLayout::NCHW})), framework::dataset::make(&quot;DataType&quot;,{DataType::F32})), shape_a, output_tile, data_layout, data_type)</td></tr>
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<tr class="memitem:aacee712d2df2d32d897c49954b2a2748"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation.xhtml#aacee712d2df2d32d897c49954b2a2748">FIXTURE_DATA_TEST_CASE</a> (RunSmall, CLWinogradFilterTransformFixture, framework::DatasetMode::ALL, combine(combine(framework::dataset::concat(framework::dataset::concat(combine(datasets::Small3x3Shapes(), framework::dataset::make(&quot;OutputTile&quot;, Size2D(2U, 2U))), combine(datasets::Small3x3Shapes(), framework::dataset::make(&quot;OutputTile&quot;, Size2D(4U, 4U)))), combine(datasets::Small5x5Shapes(), framework::dataset::make(&quot;OutputTile&quot;, Size2D(4U, 4U)))), framework::dataset::make(&quot;DataLayout&quot;,{DataLayout::NCHW})), framework::dataset::make(&quot;DataType&quot;,{DataType::F32})))</td></tr>
<tr class="separator:aacee712d2df2d32d897c49954b2a2748"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ac88e837292234e114e1ff61a9f59168e"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation.xhtml#ac88e837292234e114e1ff61a9f59168e">FIXTURE_DATA_TEST_CASE</a> (RunLarge, CLWinogradFilterTransformFixture, framework::DatasetMode::NIGHTLY, combine(combine(framework::dataset::concat(framework::dataset::concat(combine(datasets::Large3x3Shapes(), framework::dataset::make(&quot;OutputTile&quot;, Size2D(2U, 2U))), combine(datasets::Large3x3Shapes(), framework::dataset::make(&quot;OutputTile&quot;, Size2D(4U, 4U)))), combine(datasets::Large5x5Shapes(), framework::dataset::make(&quot;OutputTile&quot;, Size2D(4U, 4U)))), framework::dataset::make(&quot;DataLayout&quot;,{DataLayout::NCHW})), framework::dataset::make(&quot;DataType&quot;,{DataType::F32})))</td></tr>
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<tr class="separator:af19d957a58b176c2463ebd186d8ba5f5"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a8bc6505e8a48da25d9f9c24c2a99d17a"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation.xhtml#a8bc6505e8a48da25d9f9c24c2a99d17a">DATA_TEST_CASE</a> (Configuration, framework::DatasetMode::ALL, combine(framework::dataset::concat(datasets::SmallWinogradOutputTransformDataset(), datasets::LargeWinogradOutputTransformDataset()), framework::dataset::make(&quot;DataType&quot;,{DataType::F32})), shape_a, winograd_info, data_type)</td></tr>
<tr class="separator:a8bc6505e8a48da25d9f9c24c2a99d17a"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ad82770ec8ae1c4a6b5f61c26a9944f6a"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation.xhtml#ad82770ec8ae1c4a6b5f61c26a9944f6a">FIXTURE_DATA_TEST_CASE</a> (RunSmall, CLWinogradOutputTransformFixture, framework::DatasetMode::ALL, combine(datasets::SmallWinogradOutputTransformDataset(), framework::dataset::make(&quot;DataType&quot;,{DataType::F32})))</td></tr>
<tr class="separator:ad82770ec8ae1c4a6b5f61c26a9944f6a"><td class="memSeparator" colspan="2">&#160;</td></tr>
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<tr class="memitem:a772bcae7c1909a56cc65d91b2b8452af"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation.xhtml#a772bcae7c1909a56cc65d91b2b8452af">zip</a> (zip(zip(zip(zip(framework::dataset::make(&quot;InputInfo&quot;,{TensorInfo(TensorShape(17U, 31U, 2U), 1, DataType::F16), TensorInfo(TensorShape(17U, 31U, 2U), 1, DataType::F32), TensorInfo(TensorShape(23U, 27U, 5U, 4U), 1, DataType::F32), TensorInfo(TensorShape(16U, 16U, 8U), 1, DataType::F32), TensorInfo(TensorShape(33U, 27U, 7U, 4U), 1, DataType::F32)}), framework::dataset::make(&quot;WeightsInfo&quot;,{TensorInfo(TensorShape(3U, 3U, 2U, 19U), 1, DataType::F32), TensorInfo(TensorShape(3U, 3U, 2U, 19U), 1, DataType::QASYMM8), TensorInfo(TensorShape(3U, 3U, 5U, 21U), 1, DataType::F32), TensorInfo(TensorShape(3U, 3U, 8U, 16U), 1, DataType::F32), TensorInfo(TensorShape(5U, 5U, 7U, 16U), 1, DataType::F16)})), framework::dataset::make(&quot;BiasesInfo&quot;,{TensorInfo(TensorShape(19U), 1, DataType::F32), TensorInfo(TensorShape(19U), 1, DataType::F32), TensorInfo(TensorShape(21U), 1, DataType::F32), TensorInfo(TensorShape(16U), 1, DataType::F32), TensorInfo(TensorShape(16U), 1, DataType::F32)})), framework::dataset::make(&quot;OutputInfo&quot;,{TensorInfo(TensorShape(17U, 31U, 19U), 1, DataType::F32), TensorInfo(TensorShape(15U, 15U, 19U), 1, DataType::F32), TensorInfo(TensorShape(21U, 25U, 21U, 4U), 1, DataType::F32), TensorInfo(TensorShape(16U, 16U, 16U), 1, DataType::F32), TensorInfo(TensorShape(11U, 12U, 16U, 4U), 1, DataType::F32)})), framework::dataset::make(&quot;ConvInfo&quot;,{PadStrideInfo(1, 1, 1, 1), PadStrideInfo(1, 1, 1, 1), PadStrideInfo(1, 2, 0, 0), PadStrideInfo(1, 1, 1, 1), PadStrideInfo(1, 1, 1, 0)})), framework::dataset::make(&quot;Expected&quot;,{false, false, false, false, false}))</td></tr>
<tr class="separator:a772bcae7c1909a56cc65d91b2b8452af"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a233edcdeb8756481b8d91f7728c70789"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation.xhtml#a233edcdeb8756481b8d91f7728c70789">FIXTURE_DATA_TEST_CASE</a> (RunSmall, CLWinogradConvolutionLayerFastMathFixture, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::SmallWinogradConvolutionLayer3x3Dataset(), framework::dataset::make(&quot;DataType&quot;,{DataType::F32})), framework::dataset::make(&quot;ActivationLayerInfo&quot;,{ActivationLayerInfo()})))</td></tr>
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<tr class="memitem:a53f261da82bbfe025b3eda2e3286abcd"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation.xhtml#a53f261da82bbfe025b3eda2e3286abcd">FIXTURE_DATA_TEST_CASE</a> (RunLarge, CLWinogradConvolutionLayerFastMathFixture, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeWinogradConvolutionLayer3x3Dataset(), framework::dataset::make(&quot;DataType&quot;,{DataType::F32})), framework::dataset::make(&quot;ActivationLayerInfo&quot;,{ActivationLayerInfo()})))</td></tr>
<tr class="separator:a53f261da82bbfe025b3eda2e3286abcd"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a6be73592ec9551093376571488cb4fd2"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation.xhtml#a6be73592ec9551093376571488cb4fd2">combine</a> (combine(datasets::SmallWinogradConvolutionLayer5x5Dataset(), framework::dataset::make(&quot;DataType&quot;,{DataType::F32})), framework::dataset::make(&quot;ActivationLayerInfo&quot;,{ActivationLayerInfo()})))</td></tr>
<tr class="separator:a6be73592ec9551093376571488cb4fd2"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a025fb3e3793914934a99af68ee5da7d5"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation.xhtml#a025fb3e3793914934a99af68ee5da7d5">FIXTURE_DATA_TEST_CASE</a> (RunLarge, CLWinogradConvolutionLayerFastMathFixture, framework::DatasetMode::NIGHTLY, combine(combine(datasets::LargeWinogradConvolutionLayer5x5Dataset(), framework::dataset::make(&quot;DataType&quot;,{DataType::F32})), framework::dataset::make(&quot;ActivationLayerInfo&quot;,{ActivationLayerInfo()})))</td></tr>
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<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="var-members"></a>
Variables</h2></td></tr>
<tr class="memitem:ae008e90eb6906fa3526213bc860f6cc5"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation.xhtml#ae008e90eb6906fa3526213bc860f6cc5">input_info</a></td></tr>
<tr class="separator:ae008e90eb6906fa3526213bc860f6cc5"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a25cae7166733a51d1354f3f395652782"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation.xhtml#a25cae7166733a51d1354f3f395652782">output_info</a></td></tr>
<tr class="separator:a25cae7166733a51d1354f3f395652782"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a809d18ccde99d938a68cb90ef53aa749"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation.xhtml#a809d18ccde99d938a68cb90ef53aa749">winograd_info</a></td></tr>
<tr class="separator:a809d18ccde99d938a68cb90ef53aa749"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aa6e67bddae371a5731f6d4002e787299"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation.xhtml#aa6e67bddae371a5731f6d4002e787299">expected</a></td></tr>
<tr class="separator:aa6e67bddae371a5731f6d4002e787299"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a43c38c81ff3058e36ceb9904a944d1ea"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation.xhtml#a43c38c81ff3058e36ceb9904a944d1ea">bias_info</a></td></tr>
<tr class="separator:a43c38c81ff3058e36ceb9904a944d1ea"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a7cb842ebfe255726066039853a4322f0"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation.xhtml#a7cb842ebfe255726066039853a4322f0">weights_info</a></td></tr>
<tr class="separator:a7cb842ebfe255726066039853a4322f0"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:acbf8f8a6dd185de04c1981c57a8963cf"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation.xhtml#acbf8f8a6dd185de04c1981c57a8963cf">conv_info</a></td></tr>
<tr class="separator:acbf8f8a6dd185de04c1981c57a8963cf"><td class="memSeparator" colspan="2">&#160;</td></tr>
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